Wireless energy transfer for energy harvesting communications will introduce a new breed of wireless networks with extended lifetime, deployable in challenging conditions or locations including in-infrastructure and in-body applications. Such nodes will not only harvest energy from nature to continually recharge their batteries but will be able to share energy with similar devices in the network via wireless energy transfer for uninterrupted and perpetual operation.

Energy cooperation through wireless energy transfer adds a significant new dimension on top of energy harvesting from natural resources, by giving nodes the ability to transfer some of their energies to neighboring nodes as needed. This technology enables the energy-receiving nodes to harvest energy from a man-made source via a targeted and optimized energy transfer process. As such, this technology is useful as an additional source of energy and as a mechanism to regulate the pace of incoming energy when ambient resources fluctuate. It also could be the only dependable energy source when ambient resources are not sufficient.

Ulukus will investigate communication theory, optimization and networking aspects of energy harvesting wireless networks with wireless energy transfer to determine the optimum transmission, scheduling, reception and networking methods for such systems. Her team will determine optimum wireless energy transfer times and amounts, on top of the energy harvesting profile of the user from natural energy sources, so as to optimize the overall energy arrival profile at the energy receiving node, to maximize the given objective of the user.

In addition, the Ulukus team will investigate energy cooperation schemes at the battery level that together with signal cooperation schemes at the physical layer improve the end-to-end throughput of the system in small to medium size networks. Finally, the researchers will study joint energy and information routing in multi-hop cooperative wireless networks, where energy and information flow together in the system due to wireless energy transfer. They will develop practical, distributed, local measurement-based, back-pressure type algorithms for the control of both data and energy queues in the network.